Case study
10,000 scenarios before putting a train on the tracks
10,000 scenarios simulated before committing equipment and contracts.
- Client
- Intermodal logistics operator
- Sector
- Logistics & customs
- Size
- Large company
- Area
- Europe
- Solution
- Intelligence & forecasting
- Period
- 2025
10,000
Monte Carlo scenarios to decide the service
01 · Problem
Where we started
A single average scenario hides the worst cases.
02 · What we built
The solution, piece by piece
Mathematical model of the service
The service, as formulas.
Monte Carlo simulation
Thousands of trials, with the risk.
Scenario comparison
Options compared.
How it works
From problem to result
The service becomes a model
Real capacity, times and costs, written as formulas.
Illustrative drawings: no client data.
03 · Where the person steps in
Management chooses the scenario
Management chooses. The model measures the risk.
Human-in-the-Loop
- Assumptions validated by the operations team
- Final choice made by management
- Model reusable for new routes
04 · Results
The project's numbers
real result
10.000
Monte Carlo scenarios simulated to decide the service
Intermodal logistics operator, 2025
Train composition, volumes and revenue of the client are confidential and are not published.